Spatial Data & Circular Plots

library(ggplot2)
library(dplyr)
library(plotly)
head(state.x77)

           Population Income Illiteracy Life Exp Murder HS Grad
Alabama          3615   3624        2.1    69.05   15.1    41.3
Alaska            365   6315        1.5    69.31   11.3    66.7
Arizona          2212   4530        1.8    70.55    7.8    58.1
Arkansas         2110   3378        1.9    70.66   10.1    39.9
California      21198   5114        1.1    71.71   10.3    62.6
Colorado         2541   4884        0.7    72.06    6.8    63.9
           Frost   Area
Alabama       20  50708
Alaska       152 566432
Arizona       15 113417
Arkansas      65  51945
California    20 156361
Colorado     166 103766

nrow(state.x77)

[1] 50

head(state.abb)

[1] "AL" "AK" "AZ" "AR" "CA" "CO"

states_map <- map_data("state")
head(states_map)

states <- as.data.frame(state.x77)
states$region <- tolower(rownames(states))
head(states)

fact_join <- left_join(states_map, states, by = "region")

p1 <- ggplot(fact_join, aes(long, lat, group = group)) + geom_polygon(aes(fill = Population), color = "white") + scale_fill_viridis_c(option = "C") + theme_classic()

ggplotly(p1)

library(cartography)
library(sp)
data("nuts2006")
summary(nuts2.spdf)

Object of class SpatialPolygonsDataFrame
Coordinates:
      min     max
x 2641758 7313157
y 1427614 5411284
Is projected: TRUE 
proj4string :
[+proj=laea +lat_0=52 +lon_0=10 +x_0=4321000 +y_0=3210000
+ellps=GRS80 +units=m +no_defs]
Data attributes:
      id           
 Length:310        
 Class :character  
 Mode  :character  

head(nuts2.df)

p2 <- plot(nuts0.spdf, border = NA, col = NA, bg = "#A6CAE0")
p2 <- p2 + plot(world.spdf, border = NA, col = "#E3DEBF", add = TRUE)

p2 <- p2 + plot(nuts0.spdf, border = "grey80", col = "#D1914D", add = TRUE)

p2 <- p2 + propSymbolsLayer(spdf = nuts0.spdf, df = nuts0.df, var = "pop2008", symbols = "circle", col = "#920000", legend.pos = "right", legend.title.txt = "Total\npopulation (2008)", legend.style = "c")

p2 <- p2 + layoutLayer(title = "European Countries Population", author = "cartography", sources = "Eurostat, 2008", scale = NULL, south = TRUE)

p2

integer(0)

library(geofacet)
head(state_ranks)

p3 <- ggplot(state_ranks, aes(variable, rank, fill = variable)) + geom_col() + coord_flip() + theme_bw() + facet_geo(~state, grid = "us_state_grid2")

p3

library(statebins)
library(tidyverse)
data("USArrests")
head(USArrests)

USArrests$state <- rownames(USArrests)

p4 <- statebins(USArrests, value_col = "Assault", name = "Assault") + theme_statebins(legend_position = "right")

p4

rect <- data.frame(x = 50, y = 50)
line <- data.frame(x = c(1, 200), y = c(100, 1))

p5 <- ggplot(mapping = aes(x, y)) + geom_tile(data = rect, aes(width = 50, height = 50)) + geom_line(data = line)

p5 + coord_polar("x")

p5 + coord_polar("y")

head(mtcars)

p6 <- ggplot(mtcars, aes(x = "", fill = factor(carb))) + geom_bar(width = 1)

ggplotly(p6)

p6 + coord_polar()

p6 + coord_polar(theta = "y")

p7 <- ggplot(mtcars, aes(x = factor(cyl), fill = factor(cyl))) + geom_bar(width = 1, color = "black")

ggplotly(p7)

p7 + coord_polar()

p7 + coord_polar(theta = "y")

head(diamonds)

p8 <- ggplot(diamonds, aes(x = "", fill = color)) + geom_bar(width = 1)

ggplotly(p8)

p8 + coord_polar()

p8 + coord_polar(theta = "y")

p9 <- ggplot(diamonds, aes(x = clarity, fill = cut)) + geom_bar(width = 1)

ggplotly(p9)

p9 + coord_polar()

p9 + coord_polar(theta = "y")

library(gcookbook)
head(wind)

p10 <- ggplot(wind, aes(x = DirCat, fill = SpeedCat)) + geom_histogram(binwidth = 15, boundary = -7.5)

ggplotly(p10)

p10 + coord_polar()

p10 + coord_polar(theta = "y")